Tuesday, May 5, 2009

Photoshop: How to Read Histograms



I will be outlining some of the information you can read straight off a histogram with very little understanding of what it is showing. It is a very underused tool, mainly because most people using digital cameras do not under and what to look for and so they ignore it.

Most digital cameras come with a histogram display, but what exactly is a histogram?

Simply put - it is a representation of the colours within your image. On the left, black, on the right, white; with every colour in between. The vertical height of any column shows how many pixels of that exact colour there are in your image at each brightness setting.

Now that you know what you are looking at, I'll show examples of some common things you can see.

Exposure

Ok - It can be hard to tell on your small LCD display whether an image is exposed correctly. Just take a look at the histogram and you will see quickly.

Overexposure

There is a clear bias here towards the white end of the spectrum - unless your image is of something which is supposed to have a lot of near-white and pure white, it's almost certainly overexposed and any details in the picture will be lost to highlights.


Underexposure

There is a clear bias here towards the black end of the spectrum - unless your image is supposed to be of something dark, it's almost certainly underexposed and any details in the picture will be lost to shadows and will be very hard to recover properly on your computer.

Contrast

Over-contrasting

A histogram like this shows that you have failed to capture the dynamic range of the subject matter, with no distinctly obvious spikes in colour.


Under-contrasting

A lack of contrast will make your picture look hazy and flat. This histogram, for example, has no shadows or highlights and would have no depth. I will conclude with an example of what your histogram should look like if exposure and contrast are correct.



Defined spikes of some colours, no overwhelming shadows or highlights and a full spectral range.

This concludes, I hope this simplfied look at histograms will help you understand and use them more.

0 comments:

Post a Comment

 

Webdoor. Copyright 2009 All Rights Reserved Revolution Two Church theme by Brian Gardner Blog Skins